Finger opened by saying that he and Dutta were prompted to write the book Ask, Measure, Learn following lessons learned managing their former company, Fisheye Analytics. The company, which mined media data, provided services to the Organization for Economic Co-operation and Development (OECD), FIFA, and the Olympic Committee and was acquired by the WPP group in 2013.

“Any company has a lot of data; most of it irrelevant,” said Finger. “Big data can be a big pain, but I believe data analytics will be bigger than the launch of the Internet.”

Having obtained advance approval, Finger then launched into revealing results from a data mine of Johnson students’ LinkedIn accounts and presented photos of the first student to join LinkedIn, the student who was “most connected,” and the student who was “most popular” based on recommendations. His findings were met with resounding applause when he pointed out that the student who has the most powerful network is the student connected to four different groups at Cornell.

During his talk, Finger encouraged students to ask the right questions, measure the right data, and then learn from results. He gave the example of Google overtaking Alta Vista in only 10 months because Google provided more targeted search results and asked the right question by determining users were searching for one website.

“The quest of the ask has not changed; it’s the business leaders who get the ask correctly whose businesses prosper,” said Finger. “The right question is actionable, time bound, and specific.”

Finger then touched on the myth of the influential person in the digital economy, explaining that someone who is well-connected and part of a vast social network may not actually “influence” others as expected.

Later in the talk he said that cause is not the same as correlation, but statistically it’s very hard to distinguish between the two. Finger closed by pointing out that even with available data, we can’t predict what humans will choose and gave the example of how difficult it is for Hollywood to predict a blockbuster film.